API Documentation

Learn how to integrate AIKVIST API into your applications

Quick Start

Get started with AIKVIST API in minutes. Our API is fully compatible with OpenAI's interface.

1. Get Your API Key

2. Install SDK

Install the OpenAI SDK or use our compatible endpoints.

bash

pip install openai

3. Make Your First Request

Start making requests with your preferred model.

Authentication

All API requests require authentication using your API key.

API Key Header

Include your API key in the Authorization header:

http

Authorization: Bearer YOUR_API_KEY

Keep your API keys secure and never expose them in client-side code.

Chat Completions

Generate conversational responses using various AI models.

Endpoint

http

POST https://api.aikvist.com/v1/chat/completions

Request Parameters

modelID of the model to use

messagesArray of message objects

temperatureSampling temperature (0-2)

max_tokensMaximum tokens to generate

streamEnable streaming responses

Example Request

typescript

import OpenAI from 'openai';

// OpenAI 风格 Base URL
const client = new OpenAI({
  baseURL: 'https://api.aikvist.com/v1',
  apiKey: process.env.OPENLLM_API_KEY,
});

// OpenRouter 风格也同样支持:
// baseURL: '/v1'

const response = await client.chat.completions.create({
  model: 'gpt-4',
  messages: [
    { role: 'user', content: 'Hello!' }
  ],
});

console.log(response.choices[0].message.content);

Python Example Request

python

from openai import OpenAI

# OpenAI 风格 Base URL
client = OpenAI(
    base_url="https://api.aikvist.com/v1",
    api_key="YOUR_API_KEY"
)

# OpenRouter 风格也同样支持:
# base_url="/v1"

response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Available Models

Access hundreds of AI models through a single API.

List Models Endpoint

http

GET https://api.aikvist.com/v1/models

Flagship Models

Latest and most capable models from major providers

Coding Specialist

Optimized for code generation and technical tasks

Reasoning Models

Advanced reasoning and complex problem-solving

Multimodal

Support for images, audio, and video inputs

Streaming Responses

Stream responses in real-time for better user experience.

Benefits of streaming:

Reduced perceived latency
Real-time feedback
Better UX for long responses

Implementation Example

typescript

const stream = await client.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: 'Tell me a story' }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content || '');
}

Anthropic Native API

AIKVIST fully supports Anthropic's native /v1/messages API format. You can use the official Anthropic SDK directly, with support for streaming and Prompt Cache.

Base URL

Set the Anthropic SDK's base_url to the following address, using your AIKVIST API Key:

http

Base URL: https://api.aikvist.com

Python SDK

python

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.aikvist.com",
    api_key="YOUR_API_KEY",
)

message = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ]
)

print(message.content[0].text)

TypeScript SDK

typescript

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://api.aikvist.com',
  apiKey: 'YOUR_API_KEY',
});

const message = await client.messages.create({
  model: 'claude-opus-4-6',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Hello, Claude!' }
  ],
});

console.log(message.content[0].text);

Streaming

Use the Anthropic SDK's stream method for streaming output:

python

with client.messages.stream(
    model="claude-opus-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Tell me a story"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Prompt Cache

Enable prompt caching with the cache_control parameter to reduce repeated token costs:

python

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system=[{
        "type": "text",
        "text": "You are a helpful assistant...(long system prompt)...",
        "cache_control": {"type": "ephemeral"}
    }],
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

# Check cache usage
print(f"Cache read: {message.usage.cache_read_input_tokens}")
print(f"Cache creation: {message.usage.cache_creation_input_tokens}")

cURL Example

Call the API directly using HTTP:

bash

curl https://api.aikvist.com/v1/messages \
  -H "x-api-key: YOUR_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-6",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Supported Models

The following Claude models are currently available via the native API format:

Claude Opus 4

claude-opus-4-6

Claude Sonnet 4

claude-sonnet-4-6

Claude Haiku 3.5

claude-haiku-4-5

Error Handling

Understand and handle API errors effectively.

Common Error Codes

401401 Unauthorized - Invalid API key
429429 Too Many Requests - Rate limit exceeded
500500 Internal Server Error - Service error
503503 Service Unavailable - Temporary outage

Best Practices

Implement exponential backoff for retries
Handle rate limits gracefully
Log errors for debugging

Pricing & Billing

Transparent pricing based on actual usage.

Model	Input Price	Output Price
GPT-4	$5.00	$15.00
GPT-3.5 Turbo	$0.50	$1.50
Claude 3 Opus	$15.00	$75.00

per 1M tokens

Pay-as-you-go pricing with no subscription required.

Track your usage and costs in real-time from the dashboard.

SDKs & Libraries

Official and community-maintained SDKs for popular languages.

Official SDKs

Python

Use the official OpenAI Python library

pip install openai

Node.js / TypeScript

Use the official OpenAI Node.js library

npm install openai

Popular Frameworks

•

LangChain: LangChain integration for building AI applications

•

Vercel AI SDK: Vercel AI SDK for React and Next.js applications

Rate Limits

API usage limits to ensure fair access and service stability.

Tier	Requests	Tokens
Free	100 req/day	100K tokens/day
Pro	10,000 req/day	10M tokens/day

Rate limit information is included in response headers:

http

X-RateLimit-Limit: 10000
X-RateLimit-Remaining: 9999
X-RateLimit-Reset: 1640995200

Support & Resources

Community

Join our Discord community for help and discussions

Email Support

Contact our team at support@aikvist.com

Status Page

Check real-time API status and uptime

Changelog

Stay updated with latest features and improvements